Enhancing the spectral efficiency and energy efficiency of underwater channel communication by optimal cooperative spectrum sensing using hybrid optimization

2020 ◽  
Vol 33 (11) ◽  
pp. e4417 ◽  
Author(s):  
Sanapala Umamaheshwararao ◽  
Muvvala Naga Venkata Siva Santosh Kumar ◽  
Madhu Ramarakula
Keyword(s):  
Energy Efficiency ◽  
Spectrum Sensing ◽  
Spectral Efficiency ◽  
Cooperative Spectrum Sensing ◽  
Hybrid Optimization

scholarly journals Energy Efficiency Under Double Deck Relay Assistance on Cluster Cooperative Spectrum Sensing in Hybrid Spectrum Sharing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 41298-41308 ◽  
Author(s):  
Seleman Daudi Arthur Nkalango ◽  
Hui Zhao ◽  
Yuxin Song ◽  
Tianqi Zhang
Keyword(s):  
Energy Efficiency ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Cooperative Spectrum Sensing

Joint Spectrum Sensing and Data Transmission Optimization for Energy Efficiency in Cognitive Radio Sensor Networks: A Dynamic Cooperative Method

2015 ◽  
Vol 19 (2) ◽  
pp. 197-204 ◽  
Author(s):  
Yi Li ◽  
◽  
Jun Peng ◽  
Fu Jiang ◽  
Kaiyang Liu ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Data Transmission ◽  
Cooperative Spectrum Sensing ◽  
Optimization Method ◽  
Joint Optimization ◽  
Transmission Scheme ◽  
Cognitive Radio Sensor Networks

To address the inherent energy constraint in cognitive radio sensor networks, a novel joint optimization method of spectrum sensing and data transmission for energy efficiency is investigated in this paper. To begin with, a cooperative spectrum sensing scheme based on dynamic censoring is employed to shorten sensing time and save unnecessary spectrum sensing energy. Then to jointly optimize the energy efficiency, the distortion constrained probabilistic transmission scheme is utilized. Afterwards the sensing threshold solving issue can be formulated as a nonlinear minmax optimization problem with the detection probability and false alarm probability constraints. Solving by the Matlab software with the free OPTI toolbox, simulation results demonstrate that significant energy can be saved via the the proposed joint optimization method in various mobile cloud scenarios.

On the Trade-Off Between Security and Energy Efficiency in Cooperative Spectrum Sensing for Cognitive Radio

2013 ◽  
Vol 17 (8) ◽  
pp. 1564-1567 ◽  
Author(s):  
S. Althunibat ◽  
V. Sucasas ◽  
H. Marques ◽  
J. Rodriguez ◽  
R. Tafazolli ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Trade Off

scholarly journals A Robust and Energy Efficient Cooperative Spectrum Sensing Scheme in Cognitive Wireless Sensor Networks

2015 ◽  
Vol 7 (3) ◽  
pp. 140 ◽  
Author(s):  
Shaoyang Men ◽  
Pascal Chargé ◽  
Sébastien Pillement
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Evaluation Method ◽  
Cooperative Spectrum Sensing ◽  
Wireless Sensor ◽  
Hidden Terminal ◽  
Cognitive Wireless Sensor Networks

Cooperative spectrum sensing (CSS) is able to effectively solve the hidden terminal, depth attenuation, multipath shadows and other issues which are not addressed by the single-user sensing. Therefore, it has attracted a large amount of interest and several CSS algorithms have been proposed. However, they are not specifically tailored for cognitive wireless sensor networks (CWSNs) where transmission reliability, power management and interference avoidance are critical issues. In this paper, we propose a robust and energy efficient CSS scheme in CWSNs. Firstly, taking into account the limited energy of sensor node, especially the mobile node, we introduce the nodes of the network into multiple clusters for the CSS in order to save energy consumed in reporting results and exchanging information and extend the lifetime of the network. Secondly, we consider that some cognitive nodes may not work as expected. Hence, facing the problem of faulty nodes in clusters, we propose an evaluation method which considers simultaneously the node reliability and the mutually supportive degree among different nodes to support adapted decisions. Finally, after removing the node of low credibility, the energy efficiency and reliability of each cluster are improved significantly. Simulation results allow to validate that the proposed method outperforms the state of the art in energy efficiency and detection reliability, even in presence of faulty nodes.

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